The technique known as road-mapping is used in the selective catheterization of vessels in the framework of an interventional treatment. In these minimally invasive, angiographic interventions, an image of a patient's vasculature is obtained for use as a “road map,” to assist a physician to efficiently guide or navigate instruments such as catheters or guide-wires through the patient's vasculature. Intravascular procedures are typically performed using a C-arm x-ray imaging system which includes an adjustable x-ray source and an x-ray detector.
Image based navigation using the road-mapping technique can be characterized by the three types of images involved: vessel images (road map of patient's vasculature), fluoroscopy images and navigation images. The vessel image is acquired by injecting a quantity of contrast agent (typically iodine) into the blood stream during x-ray acquisition to visualize the patient's vasculature. This image is retained as a “road map” image. Fluoroscopy images are acquired without the injection of a contrast agent and typically depict dense structures such as bones and instruments. The navigation image is then computed by combining the vessel image with the fluoroscopy image to visualize the live instruments in the context of the vasculature. Presently, the road mapping technique finds application in the prior art in both 2D and 3D image based navigation techniques, both of which are briefly described as follows.
In a 2D image processing application, a series of vessel images is acquired by injecting a relatively small quantity of contrast agent (typically iodine) into the blood to opacify the vessel tree during image acquisition. The C-arm is kept stationary during the acquisition. One vessel image is selected to serve as a so-called “road map”. The navigation images are created by combining the single road map image with each live fluoroscopy image for guiding instrumentation (e.g., guide wires, catheters) throughout the vasculature, in real-time.
One drawback associated with the prior art 2D image processing application is that re-positioning of the C-arm to resolve ambiguous plane turns of vessels is done “blindly” on a trial-and-error basis. In other words, a physician or operator makes an educated guess as to how to re-position the C-arm to resolve ambiguity through plane turns of the vessels. Due to the uncertainty of the trial-and-error approach, each trial may have intended or unintended results for navigating through the vasculature. Each trial requires the injection of contrast media at each step. This is highly undesirable from the patient's perspective in that multiple injections of contrast media may or may not be well tolerated in the patient. A further disadvantage of the prior art 2D image processing application is that the single “road map” image obtained at the outset of the procedure is a plain-projection image devoid of depth information.
In a 3D image processing application, a quantity of contrast agent is injected to opacify the vessels. A C-arm is then rotated on a circular trajectory around the patient during the injection. In this manner, a series of high-quality images are acquired, each depicting the vasculature from a different angle. In a subsequent processing step, all acquired images are sent to a reconstruction unit, where a 3D image (volume) of the vessel tree is computed. This 3D image is retained and serves as the vessel image of the 3D road-mapping technique. A 2D vessel image showing the vasculature from any angle can be obtained by re-projecting the 3D vessel image. Similar to the 2D road-mapping technique, this 2D vessel image is combined with a fluoroscopy image to obtain the navigation image. A drawback of the 3D image processing application is that the 3D image of the vasculature has to be acquired such that the result is clinically useful, e.g. depict the vessel tree in pristine quality. In order for the 3D image to be clinically useful, several prerequisites have to be fulfilled. First, the C-arm apparatus must be rotated over an angular range of 180 degrees, at a minimum, to obtain a clinically useful reconstruction of the vessel tree. This necessitates a relatively long processing time (e.g., on the order of 7 seconds) during which a significant amount of contrast agent is injected into the patient. Second, the quality of the 3D reconstruction is proportional to the number of images acquired during the rotational run. In other words, for the highest quality 3D reconstruction, a significant amount of projections have to be acquired, which results in increased radiation exposure to the patient. Third, the time it takes to compute a 3D reconstruction of the vessel tree is proportional to the number of 2D projections input to the reconstruction unit. For a high quality reconstruction, computation time can amount to a significant number. Fourth, there should be as little as possible motion of the anatomy during image acquisition. Too much motion will result in a 3D reconstruction of poor quality. Fifth, there should be no metallic objects, such as stents or coils in the field of view. These objects typically cause streak artifacts in the 3D reconstruction which may diminish image quality.
It would therefore be desirable to develop an improved computer-implemented method of image based navigation for use during an interventional medical procedure that is more advanced than the prior art 2D imaging method, discussed above, and provides guidance in situations where one or more of the above prerequisites of the prior art 3D method, discussed above, are not fulfilled.